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full – AI Model by GoodBoy9 | AlphaNeural AI

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ScalpPipeline (`pipeline.py`)

Refactored pipeline combining all steps into a single class.

Usage

python pipeline.py --pixel_ratio 2.54

Arguments:

--root_dir: Root directory of the project (default: .)
--pixel_ratio: Pixel to micrometer ratio (default: 2.54)

Dependencies (Files)

The pipeline requires the following files and directories to exist:

Input Images:
- datasets/data/ : Directory containing input images (.jpg, .jpeg, .png).
Model Weights:
- segmentation/model/U2NET.pth : Pre-trained U2NET model.
- sam_vit_h_4b8939.pth : SAM (Segment Anything Model) checkpoint (ViT-H).
Code Modules:
- segmentation/data_loader.py : Data loading utilities for U2NET.

Output

Results are saved in:

datasets/seg_train/ (U2NET masks)
prediction/sam_result/sam_val/ (SAM masks)
prediction/ensemble_result/ensemble_val/ (Ensemble masks)
alopecia/thickness_result/ (Thickness data & visualization)
alopecia/count_result/ (Hair count CSV & visualization)